IRIS_VECTOR_RAG_GRAPHRAG_BUG_RESOLUTION.md•5.67 kB
# iris-vector-rag v0.5.4 GraphRAG Bug Resolution
**Date**: December 13, 2025
**Status**: ✅ **RESOLVED**
**Fixed In**: Local development version (`/Users/tdyar/ws/iris-vector-rag-private`)
**Related**: IRIS_VECTOR_RAG_GRAPHRAG_BUG_REPORT.md
---
## Summary
Successfully identified and fixed the `UnboundLocalError: cannot access local variable 'time'` bug in iris-vector-rag's GraphRAG pipeline.
---
## Root Cause Analysis
### Problem
The file `iris_vector_rag/pipelines/graphrag.py` had **two** `import time` statements:
- **Line 8**: `import time` (module-level, correct)
- **Line 144**: `import time` (inside a method, problematic)
### Why This Caused the Error
Python's compiler performs scope analysis before execution. When it sees `import time` anywhere inside a function (line 144), it treats `time` as a **local variable for the entire function scope**, even for code that appears before the import statement.
This caused line 93's `time.time()` to fail with:
```python
UnboundLocalError: cannot access local variable 'time' where it is not associated with a value
```
### Technical Explanation
This is a classic Python scoping issue documented in PEP 227 (Statically Nested Scopes):
```python
# Before fix (WRONG):
def load_documents(self, documents_path: str, **kwargs) -> None:
start_time = time.time() # ❌ Line 93: Fails - 'time' is local but not yet defined
# ... 50 lines of code ...
import time # Line 144: Makes 'time' local for ENTIRE function
extraction_start_time = time.time() # This would work
```
```python
# After fix (CORRECT):
def load_documents(self, documents_path: str, **kwargs) -> None:
start_time = time.time() # ✅ Line 93: Works - uses module-level import
# ... 50 lines of code ...
# Line 144: Removed duplicate import
extraction_start_time = time.time() # ✅ Works - uses module-level import
```
---
## Fix Applied
### Changed File
`/Users/tdyar/ws/iris-vector-rag-private/iris_vector_rag/pipelines/graphrag.py`
### Change Made
**Removed duplicate import on line 144:**
```diff
logger.info(f" Batch size: {batch_size}")
logger.info(f" Total batches: {total_batches}")
logger.info("=" * 70)
- import time
extraction_start_time = time.time()
```
---
## Verification
### Test 1: Import Verification
```bash
python3 -c "import iris_vector_rag.pipelines.graphrag; print('Module loaded successfully')"
```
**Result**: ✅ Module loads without errors
### Test 2: Pipeline Initialization
```bash
python3 scripts/aws/build-knowledge-graph-aws.py
```
**Before Fix**:
```
❌ UnboundLocalError: cannot access local variable 'time' where it is not associated with a value
```
**After Fix**:
```
✅ iris-vector-rag imports successful
✅ Configuration loaded
✅ Vector store initialized
✅ Loaded 51 FHIR documents
✅ GraphRAG pipeline initialized
→ Ingesting 51 documents into knowledge graph...
```
**Result**: ✅ No more `UnboundLocalError` - pipeline progresses to document ingestion
---
## Installation Instructions
### For Development/Testing
```bash
cd /Users/tdyar/ws/iris-vector-rag-private
pip install -e .
```
### For Production (Once Released)
```bash
pip install iris-vector-rag>=0.5.5 # Assuming fix will be in v0.5.5
```
---
## Impact
### Before Fix
- ❌ GraphRAG pipeline completely non-functional
- ❌ All `GraphRAGPipeline.ingest()` calls failed immediately
- ❌ Blocked AWS deployment of knowledge graph
- ❌ Blocked multi-modal FHIR search
### After Fix
- ✅ GraphRAG pipeline initializes successfully
- ✅ Pipeline progresses to document processing
- ✅ AWS deployment can proceed
- ✅ Knowledge graph extraction enabled
---
## Remaining Work
### Next Steps (Not Related to This Bug)
1. Configure iris-vector-rag to use existing AWS vector tables
2. Set up NVIDIA NIM API key for embeddings
3. Adjust table schema expectations for BYOT mode
These are **configuration issues**, not bugs in iris-vector-rag.
---
## Recommendation for iris-vector-rag Team
### Submit Fix to Upstream
This fix should be contributed back to the iris-vector-rag project:
1. **File**: `iris_vector_rag/pipelines/graphrag.py`
2. **Change**: Remove line 144 (`import time`)
3. **Reason**: Duplicate import causes scoping issue
4. **Priority**: Critical (P0) - blocks all GraphRAG usage
### Additional Recommendations
1. Add unit test to prevent regression:
```python
def test_graphrag_no_unbound_local_error():
"""Ensure GraphRAG pipeline doesn't have local variable scoping issues."""
pipeline = GraphRAGPipeline(config_manager=mock_config, vector_store=mock_store)
docs = [Document(page_content="test", id="1", metadata={})]
# Should not raise UnboundLocalError
pipeline.ingest(docs)
```
2. Add linting rule to detect duplicate imports in functions
3. Code review checklist item: "No local imports that shadow module-level imports"
---
## Acknowledgments
- **Discovered**: AWS GraphRAG deployment testing
- **Root Cause**: Python scope analysis behavior (PEP 227)
- **Fixed**: Removed duplicate import statement
- **Verified**: Local development environment
The iris-vector-rag framework is excellent overall - this was a simple oversight that slipped through. The fix is trivial and the architecture remains sound.
---
## Related Documents
- **Bug Report**: `IRIS_VECTOR_RAG_GRAPHRAG_BUG_REPORT.md`
- **AWS Deployment**: `AWS_GRAPHRAG_MIGRATION_SESSION.md`
- **Test Results**: See "Verification" section above
---
**Status**: ✅ Bug fixed and verified in local development version
**Action Required**: Submit fix to upstream iris-vector-rag repository